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Koley_Picture_That_Sketch_Photorealistic_Image_Generation_From_Abstract_Sketches_CVPR_2023_paper.pdf
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🔗 Source: openaccess.thecvf.com
📊 Size: 9.24 MB
👤 Author: Subhadeep Koley; Ayan Kumar Bhunia; Aneeshan Sain; Pinaki Nath Chowdhury; Tao Xiang; Yi-Zhe Song
⬇️ Downloads: 181

Summary

The approach uses a decoupled encoder-decoder training paradigm, where the decoder is a pre-trained StyleGAN trained on photos only. An autoregressive sketch mapper is trained on sketch-photo pairs to map a sketch to the StyleGAN latent space. The method introduces a fine-grained discriminative loss and a partial-aware sketch augmentation strategy to tackle the abstract nature of human sketches. The generated results are photorealistic and can be used for downstream tasks such as fine-grained sketch-based image retrieval and precise semantic editing.

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Description

The approach uses a decoupled encoder-decoder training paradigm, where the decoder is a pre-trained StyleGAN trained on photos only.

Technical Information

  • File Format: PDF
  • File Size: 9.24 MB
  • Pages: 12
  • Language: EN
  • Author: Subhadeep Koley; Ayan Kumar Bhunia; Aneeshan Sain; Pinaki Nath Chowdhury; Tao Xiang; Yi-Zhe Song
  • Total Downloads: 181
  • Last Updated: 6 days ago

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